DBMS > Badger vs. Google BigQuery vs. Informix vs. Rockset

System Properties Comparison Badger vs. Google BigQuery vs. Informix vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Large scale data warehouse service with append-only tables

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Key-value store

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Document store

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Relational DBMS
Search engine

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Website

github.com/dgraph-io/badger

cloud.google.com/bigquery

www.ibm.com/products/informix

rockset.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

cloud.google.com/bigquery/docs

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

docs.rockset.com

Developer

DGraph Labs

Google

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Rockset

Initial release

2017

2010

1984

2019

Current release

14.10.FC5, November 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free developer edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++ and Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

dynamic typing

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

APIs and other access methods

RESTful HTTP/JSON API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP REST

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authentication, authorization, and auditing controls

Access rights for users and organizations can be defined via Rockset console

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